ICARUS is an open-source student project aimed at developing a system for controlling a non-invasive 3D-printed hand prosthesis through EMG signals using deep reinforcement learning algorithms, thereby exploring the interactions between technology and the human body by leveraging concepts related to human-machine interactions.
In a Windows terminal, run the following commands to install WSL and set it up:
wsl --install -d Ubuntu
wsl -s Ubuntumkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh
~/miniconda3/bin/conda init bashAfter running the above commands, reboot WSL.
Before this step, you need to access the project's root directory with WSL.
conda update --all -y
conda create -n ICARUS python=3.11 -y
conda activate ICARUS
yes | pip install -r requirements.txtIf you want to run the API on your local machine, or even run the simulation, please refer to these READMEs :
This project has been influenced by the following works:
- TactHand (Open-source model of a 3D-printed hand prosthesis)
- InMoov (An other open-source model of a 3D-printed hand prosthesis)
- PyBullet (Open-source physics engine for Python)
- ROS (Open-source framework for robot software development)
- Gazebo (Open-source robotics simulator integrated with ROS)
- Pyomyo (Open source code for interfacing with Myo armbands)
We would like to express our gratitude to these authors for their groundbreaking work and contributions to the open-source community.
This project is licensed under the Apache License (Version 2.0).
See LICENSE for details.
If you use or reference this work, please cite it as follows:
@misc{maubras2024icarus,
title={ICARUS: Deep Reinforcement Learning Control of a Non-Invasive 3D-Printed Prosthesis using EMG Signals},
author={Juan Maubras, Erwan Duprey, Enzo Leonardo},
year={2024},
howpublished={\url{https://github.com/Elesdes/ICARUS}},
note={Unpublished manuscript},
}